CNS Seminar

Monday April 10, 2017 4:00 PM

Fast-Spiking Interneurons Regulate Ensemble Calcium and Striatum-Dependent Learning

Speaker: Anatol C. Kreitzer, Gladstone Institutes, University of California, San Francisco
Location: Beckman Behavioral Biology B180

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Fast-spiking interneurons (FSIs) are a prominent class of GABAergic cells that are embedded within disparate network architectures in the forebrain. These interneurons are believed to be essential for precise behavioral control through acute regulation of spike timing. However, their role in learning and network plasticity is less clear. Within the striatum, the primary input nucleus of the basal ganglia, loss of FSI function has been associated with involuntary movements in animals and Tourette's Syndrome in human patients. We find that, surprisingly, selective ablation of striatal FSIs is not sufficient to impair acute motor performance. Instead, loss of FSI function disrupted striatum-dependent forms of motor learning. To investigate the mechanism underlying these striatal learning deficits, we performed ex vivo optogenetic manipulations of FSIs, combined with electrophysiology and calcium imaging from striatal projection neurons (SPNs), as well as in vivo optogenetic manipulation of FSIs with Ca2+ imaging of SPNs in freely moving mice. We found that acutely silencing FSIs produced a 1.5-fold increase in  spiking, but a 7-fold increase in Ca2+ transients without altering baseline motor behavior, highlighting the potential of FSIs to control Ca2+-dependent plasticity during learning. During performance of a motor sequence task, Ca2+ transients in a subset of MSNs were aligned to specific components of the sequence. FSI silencing shifted the cellular composition of these task-aligned neuronal ensemble Ca2+ responses and increased the number of non-task-aligned Ca2+ transients, indicating that striatal FSIs play a key role in restricting Ca2+ signaling to salient behavioral events. Together, our data support a model in which striatal FSIs facilitate adaptive motor learning through coordination of task-related Ca2+ signaling and plasticity in MSN networks.



Series Computation and Neural Systems Seminar